def tf_fn(ctx_sbls):
"""
The map function for vsm.model.TfMulti. Takes a list of documents
as slices and returns a count matrix.
:param ctx_sbls: list of documents as slices.
:type ctx_sbls: list of slices
:returns: a count matrix
"""
offset = ctx_sbls[0].start
corpus = _corpus[offset: ctx_sbls[-1].stop]
slices = [slice(s.start-offset, s.stop-offset) for s in ctx_sbls]
return count_matrix(corpus, slices, _V.value)
def tf_fn(ctx_sbls):
"""
The map function for vsm.model.TfMulti. Takes a list of documents
as slices and returns a count matrix.
:param ctx_sbls: list of documents as slices.
:type ctx_sbls: list of slices
:returns: a count matrix
"""
offset = ctx_sbls[0].start
corpus = _corpus[offset:ctx_sbls[-1].stop]
slices = [slice(s.start - offset, s.stop - offset) for s in ctx_sbls]
return count_matrix(corpus, slices, _V.value)
def train(self):
"""
Counts word-type occurrences per context and stores the results in
`self.matrix`.
"""
self.matrix = count_matrix(self.corpus, self.docs, self.V)
def train(self):
"""
Counts word-type occurrences per context and stores the results in
`self.matrix`.
"""
self.matrix = count_matrix(self.corpus, self.docs, self.V)